Objective: There is an increase in electronic advertising billboards along major roads, which may cause driver distraction due to the highly conspicuous design of the electronic billboards. Yet limited research on the impact of electronic billboards on driving performance and driver behavior is available. The Swedish Transport Administration recently approved the installation of 12 electronic billboards for a trial period along a 3-lane motorway with heavy traffic running through central Stockholm, Sweden. The aim of this study was to evaluate the effect of these electronic billboards on visual behavior and driving performance. Method: A total of 41 drivers were recruited to drive an instrumented vehicle passing 4 of the electronic billboards during day and night conditions. A driver was considered visually distracted when looking at a billboard continuously for more than 2 s or if the driver looked away from the road for a high percentage of time. Dependent variables were eye-tracking measures and driving performance measures. Results: The visual behavior data showed that drivers had a significantly longer dwell time, a greater number of fixations, and longer maximum fixation duration when driving past an electronic billboard compared to other signs on the same road stretches. No differences were found for the factors day/night, and no effect was found for the driving behavior data. Conclusion: Electronic billboards have an effect on gaze behavior by attracting more and longer glances than regular traffic signs. Whether the electronic billboards attract too much attention and constitute a traffic safety hazard cannot be answered conclusively based on the present data.

Driver distraction is a contributing factor to many crashes; therefore, a real-time distraction warning system should have the potential to mitigate or circumvent many of these crashes. The objective of this paper is to investigate the usefulness of a real-time distraction detection algorithm called AttenD. The evaluation is based on data from an extended field study comprising seven drivers who drove on an average of 4351 ± 2181 km in a naturalistic setting. Visual behavior was investigated both on a global scale and on a local scale in the surroundings of each warning. An increase in the percentage of glances at the rear-view mirror and a decrease in the amount of glances at the center console were found. The results also show that visual time sharing decreased in duration from 9.94 to 9.20 s due to the warnings, that the time from fully attentive to warning decreased from 3.20 to 3.03 s, and that the time from warning to full attentiveness decreased from 6.02 to 5.46 s. The limited number of participants does not allow any generalizable conclusions, but a trend toward improved visual behavior could be observed. This is a promising start for further improvements of the algorithm and the warning strategy.

Objective: To propose a driver attention theory based on the notion of driving as a satisficing and partially self-paced task and, within this framework, present a definition for driver inattention. Background: Many definitions of driver inattention and distraction have been proposed, but they are difficult to operationalize, and they are either unreasonably strict and inflexible or suffer from hindsight bias. Method: Existing definitions of driver distraction are reviewed and their shortcomings identified. We then present the minimum required attention (MiRA) theory to overcome these shortcomings. Suggestions on how to operationalize MiRA are also presented. Results: MiRA describes which role the attention of the driver plays in the shared “situation awareness of the traffic system.” A driver is considered attentive when sampling sufficient information to meet the demands of the system, namely, that he or she fulfills the preconditions to be able to form and maintain a good enough mental representation of the situation. A driver should only be considered inattentive when information sampling is not sufficient, regardless of whether the driver is concurrently executing an additional task or not. Conclusions: The MiRA theory builds on well-established driver attention theories. It goes beyond available driver distraction definitions by first defining what a driver needs to be attentive to, being free from hindsight bias, and allowing the driver to adapt to the current demands of the traffic situation through satisficing and self-pacing. MiRA has the potential to provide the stepping stone for unbiased and operationalizable inattention detection and classification.